tlpipe.container.timestream_common.TimestreamCommon¶

class tlpipe.container.timestream_common.TimestreamCommon(files=None, mode='r', start=0, stop=None, dist_axis=0, use_hints=True, comm=None)[source]¶

Common things for the raw timestream data and timestream data.

This class hold the common data an operations for RawTimestream and Timestream. Usally you should not directly use this class, use RawTimestream or Timestream instead.

:param Same as container.BasicTod.:

Attributes

`array`	Return either a dish array or a cylinder array instance.
`attrs`	Attributes attached to this object.
`bl`	Return the blorder dataset for convenient use.
`bl_ordered_datasets`	Baseline ordered datasets.
`comm`	Reference to the MPI communicator.
`dist_axis`	Convenience for self.main_data_dist_axis.
`dist_axis_name`	Name of self.main_data_dist_axis.
`distributed`
`feed_ordered_datasets`	Feed ordered datasets.
`file`	Not a file at all but the top most `MemGroup` of the tree.
`freq`	Return the freq dataset for convenient use.
`freq_ordered_datasets`	Frequency ordered datasets.
`history`	The analysis history for this data.
`is_continuous`	Data is observed continuous in time?
`is_cylinder`	True if data is get from cylinder array.
`is_dish`	True if data is get from dish array.
`is_same_dec`	Data is observed for the same declination in the sky?
`is_same_pointing`	The antenna array is in the same pointing in az, alt?
`local_bl`	A convenience for bl.local_data.
`local_freq`	A convenience for freq.local_data.
`local_time`	A convenience for time.local_data.
`local_vis`	A convenience for vis.local_data.
`local_vis_mask`	A convenience for vis_mask.local_data.
`main_axes_ordered_datasets`	Datasets that have axis aligned with the main data.
`main_data`	The main data in the container which is a convenience for self[self.main_data_name].
`main_data_axes`	Axes of the main data.
`main_data_name`	Main data in the data container.
`main_time_ordered_datasets`	Datasets that have the first axis aligned with the main data.
`masked_vis`	Return a copy of the masked vis.
`name`	String giving the full path to this entry.
`ondisk`	Whether the data is stored on disk as opposed to in memory.
`parent`	Parent `MemGroup` that contains this group.
`pol_dict`	A dict maps polarization code to integer.
`time`	Return the jul_date dataset for convenient use.
`time_ordered_attrs`	Attributes that are different in different files.
`time_ordered_datasets`	Time ordered datasets.
`vis`	Return the main data for convenient use.
`vis_mask`	A convenience for self[‘vis_mask’].

__init__(files=None, mode='r', start=0, stop=None, dist_axis=0, use_hints=True, comm=None)[source]¶

Methods

`add_history`([history])	Create a new history entry.
`all_data_operate`(func[, copy_data])	Operation to the whole vis and vis_mask.
`apply_mask`([fill_val])	Applying vis_mask to vis with the fill_val.
`bl_data_operate`(func[, full_data, ...])	Data operation along the baseline axis.
`check_status`()	Check that data hold in this container is consistent.
`close`()	Close underlying hdf5 file if on disk.
`copy`()	Return a deep copy of this container.
`create_bl_ordered_dataset`(name, data[, ...])	Create a baseline ordered dataset.
`create_dataset`(name, \args, \\*kwargs)	Create and return a new dataset.
`create_feed_ordered_dataset`(name, data[, ...])	Create a feed ordered dataset.
`create_freq_and_bl_ordered_dataset`(name, data)	Create a frequency and baseline ordered dataset.
`create_freq_ordered_dataset`(name, data[, ...])	Create a frequency ordered dataset.
`create_group`(name)	Create and return a new group.
`create_main_axis_ordered_dataset`(axis, name, ...)	Create a axis_name ordered dataset.
`create_main_data`(data[, recreate, copy_attrs])	Create or recreate a main dataset.
`create_main_time_ordered_dataset`(name, data)	Create a main type time ordered dataset.
`create_time_and_bl_ordered_dataset`(name, data)	Create a time and baseline ordered dataset.
`create_time_and_freq_ordered_dataset`(name, data)	Create a time and frequency ordered dataset.
`create_time_ordered_dataset`(name, data[, ...])	Create a time ordered dataset.
`data_operate`(func[, op_axis, axis_vals, ...])	An overload data operation interface.
`data_select`(axis, value)	Select data to be loaded from input files along the specified axis.
`dataset_common_to_distributed`(name[, ...])	Convert a common dataset to a distributed one.
`dataset_distributed_to_common`(name)	Convert a distributed dataset to a common one.
`dataset_name_allowed`(name)	Datasets may only be created and accessed in the root level group.
`delete_a_dataset`(name)	Delete a dataset and also remove it from the hint if it is in it.
`delete_an_attribute`(name)	Delete an attribute and also remove it from the hint if it is in it.
`feed_select`([value, corr])	Select data to be loaded from inputs files corresponding to the specified feeds.
`flush`()	Flush the buffers of the underlying hdf5 file if on disk.
`freq_and_bl_data_operate`(func[, full_data, ...])	Data operation along the frequency and baseline axis.
`freq_data_operate`(func[, full_data, ...])	Data operation along the frequency axis.
`frequency_select`(value)	Select data to be loaded from input files along the frequency axis.
`from_file`(file_[, ondisk, distributed, ...])	Create data object from analysis hdf5 file, store in memory or on disk.
`from_group`([data_group, detect_subclass])	Create data object from a given group.
`get`((k[,d]) -> D[k] if k in D, ...)
`group_name_allowed`(name)	No groups are exposed to the user.
`info`()	List basic information of the data hold by this container.
`items`(() -> list of D’s (key, value) pairs, ...)
`iteritems`(() -> an iterator over the (key, ...)
`iterkeys`(() -> an iterator over the keys of D)
`itervalues`(...)
`keys`(() -> list of D’s keys)
`load_all`()	Load all attributes and datasets from files.
`load_common_attrs`()	Load common attributes from the first file.
`load_common_datasets`()	Load common datasets from the first file.
`load_main_axes_excl_main_data`()	Load main axes ordered datasets (exclude the main data).
`load_main_axes_ordered_data`()	Load main axes ordered dataset.
`load_main_data`()	Load main data from all files.
`load_time_ordered_attrs`()	Load time ordered attributes from all files.
`load_time_ordered_datasets`()	Load time ordered datasets (excepts those also in main_axes_ordered_datasets) from all files.
`redistribute`(dist_axis)	Redistribute the main time ordered dataset along a specified axis.
`require_dataset`(name, shape, dtype, \\kwargs)	Require a dataset to exist, create if it doesn’t.
`require_group`(name)	Require a group to exist, create if it doesn’t.
`save`(filename, \\kwargs)	Save data to hdf5 file.
`subset`()	Return a subset of the data as a new data container.
`subset_feed_select`([value, corr])	Select a subset of the data corresponding to the specified feeds.
`subset_frequency_select`(value)	Select a subset of the data along the frequency axis.
`subset_select`(axis, value)	Select a subset of the data along the specified axis.
`subset_time_select`(value)	Select a subset of the data along the time axis.
`time_and_bl_data_operate`(func[, full_data, ...])	Data operation along the time and baseline axis.
`time_and_freq_data_operate`(func[, ...])	Data operation along the time and frequency axis.
`time_data_operate`(func[, full_data, ...])	Data operation along the time axis.
`time_select`(value)	Select data to be loaded from input files along the time axis.
`to_disk`(filename, \\kwargs)	Return a version of this data that lives on disk.
`to_files`(outfiles[, exclude, check_status, ...])	Save the data hold in this container to files.
`to_memory`()	Return a version of this data that lives in memory.
`values`(() -> list of D’s values)